Testing a novel self-assembling data paradigm in the context of IACT data

Abstract

The process of gathering and associating data from multiple sensors or sub-detectors due to a common physical event (the process of event-building) is used in many fields, including highenergy physics and γ-ray astronomy. Fault tolerance in event-building is a challenging problem that increases in difficulty with higher data throughput rates and increasing numbers of subdetectors. We draw on biological self-assembly models in the development of a novel eventbuilding paradigm that treats each packet of data from an individual sensor or sub-detector as if it were a molecule in solution. Just as molecules are capable of forming chemical bonds, 'bonds' can be defined between data packets using metadata-based discriminants. A database - which plays the role of a beaker of solution - continually selects pairs of assemblies at random to test for bonds, which allows single packets and small assemblies to aggregate into larger assemblies. During this process higher-quality associations supersede spurious ones. The database thereby becomes fluid, dynamic, and self-correcting rather than static. We will describe tests of the selfassembly paradigm using our first fluid database prototype and data from the VERITAS γ-ray telescope.